Overestimation of closed-chamber soil CO₂ effluxes at low atmospheric turbulence

Abstract. Soil respiration (R_s) is an important component of ecosystem carbon balance, and accurate quantification of the diurnal and seasonal variation of R_s is crucial for a correct interpretation of the response of R_s to biotic and abiotic factors, as well as for estimating annual soil CO₂ efflux rates.

In this study, we measured R_s hourly for 1 year by automated closed chambers in a temperate Danish beech forest. The data showed a clear diurnal pattern of R_s across all seasons with higher rates during night-time than during daytime. However, further analysis showed a clear negative relationship between flux rates and friction velocity (u_∗) above the canopy, suggesting that R_s was overestimated at low atmospheric turbulence throughout the year due to non-steady-state conditions during measurements. Filtering out data at low u_∗ values removed or even inverted the observed diurnal pattern, such that the highest effluxes were now observed during daytime, and also led to a substantial decrease in the estimated annual soil CO₂ efflux.

By installing fans to produce continuous turbulent mixing of air around the soil chambers, we tested the hypothesis that overestimation of soil CO₂ effluxes during low u_∗ can be eliminated if proper mixing of air is ensured, and indeed the use of fans removed the overestimation of R_s rates during low u_∗. Artificial turbulent air mixing may thus provide a method to overcome the problems of using closed-chamber gas-exchange measurement techniques during naturally occurring low atmospheric turbulence conditions. Other possible effects from using fans during soil CO₂ efflux measurements are discussed. In conclusion, periods with low atmospheric turbulence may provide a significant source of error in R_s rates estimated by the use of closed-chamber techniques and erroneous data must be filtered out to obtain unbiased diurnal patterns, accurate relationships to biotic and abiotic factors, and before estimating R_s fluxes over longer timescales.